1. The Economic and Environmental Implications of Russian Sustainability Policy Victoria Alexeeva-Talebi Christophe Heyndrickx Natalia Tourdyeva Energy efficiency and sustainability policies in Russia Final project conference of the FP7 project on developing the Spatial-economic-ecological model for the assessment of sustainability policies of the Russian Federation 15 December 2011 Moscow

2. 2 Outline  Motivation & Objectives  Policy Background: Environmental Issues in Russian Federation  Environmental Module  Illustrative Simulation Runs with the Sust-Rus Model  Conclusions

3. 3 Motivation Russia is today the third largest CO2 emitter standing behind China and the United States; it is also one of the biggest emitter of SOx, NOx, VOC and PM; “Favorable” fuel mix in the Russian economy: more than 60% of CO2 emissions are generated by combustion of gas in 2005; Energy intensity (amount of energy consumed per unit of GDP) is higher than in any of the world’s 10-largest energy-consuming countries; EI in Russia is the highest even among the countries of the FSU; (a) EI in Russia vs. countries of the Former SU (1990-2005) (b) EI in Russian steel sector (2005) Source: Worldbank and IFW (2008)

4. 4 Economic risks of poor energy efficiency Decision makers’ economic risk perception includes:  Potential threats to the intention to act as a reliable energy supplier;  In the past, shortages of natural gas and electricity supply to the industry slowed down the economic growth (“the limits of growth”);  Deterioration of international competitiveness of Russian industries even during the period of strong economic recovery;  Growing burden on households and municipal budgets to pay the energy bills;

5. 5 Related risks of poor energy efficiency Adverse impacts on health and ecosystems from air pollution & acidifying emissions: Air pollution levels exceed maximum allowable concentrations in major urban areas of Russia; Acidifying emissions lead to surface water acidification (e.g. in the border areas between Russia and Norway) and to heavy damages of forests (e.g. in Norilsk). Today around 50% of total SO2 emissions come from the five largest sources in the ferrous metals production.

6. 6 Russia’s strategy to combat air pollution Improving energy efficiency: 40% reduction of Russia’s energy efficiency by 2020 compared with 2007 levels (Presedent Medvedev signed a decree in June 2008); significant increase in energy efficiency of electric power sector (government order of Prime Minister Putin 2009) ; Climate Doctrine of the Russian Federation approved in 2009: Reduction of the share of energy generated from natural gas to 46% or 47% by 2030, doubling of nuclear power capacity, limit the burning of gas produced from oil wells, increase the use of renewable energy in electricity production to 4,5% by 2020; Compliance with international agreements (e.g. UNFCCC / Kyoto; UNECE Convention on Long-Range Transboundary Air Pollution / 1994 Oslo Protocol: 40% SO2 reduction compared to 1980 levels) ;

7. 7 Literature review & objectives of the study CGE-based simulation studies (global & single country models): Bayar et al. (2010) and Orlov et al. (2011): Assessing energy policy and carbon emissions in Russia; Böhringer et al. (2007), Lokhov and Welsch (2008): Analyzing “where-flexibility” & “hot air for sale” potential; Paltsev (2011): Russia’s natural gas export potential up to 2050 and impact of global and sub-global climate regimes; Simulation model development for Russia: “state of the art” So far, regionally disaggregated model for Russia at the level of federal districts which captures multi-gas emissions is not available;

8. 8 EnvModule in the SUST-RUS model SUST-RUS includes three environmental dimensions:  Global: climate change (CO2 emissions)  Restrictions in the analysis of global warming policies and damage valuation: SUST- RUS is not a global model, i.e. RoW is represented at an aggregated level and is exogenous.  Regional and local (transboundary effects): emissions of SO2 and NOX depositions and ambient air concentrations (deposition of acidifying emissions, PM)  Analysis of trade-off and synergies between global warming and acid rain policies (co- benefits of climate policies)

9. 9 EnvModule: Data and model parametrization Modelling emissions: CO2, SO2, NOx and PM emissions are related to the fuel input used in production of sectors and in consumption of households; Data (emissions-related) TER Database from Goskomstat (2006) –Energy consumption in physical units at the disaggregated sectoral and regional (federal) level; Beyond2020 Database from IEA (2010) –Input-specific emission factors & calculation methodology; emissions levels; National statistical publications from Goskomstat: emissions for SO2, NOx and PM.

10. 10 Abatement options in Sust-Rus model (1)  Decline in production: environmental constraint → higher selling prices → demand for intermediates decreases → output reduction  Technological update: exogenously given technological change, e.g. leading to higher energy efficiency  Substitution of fuels within existing technologies: production of sectors is modeled via nested CES production functions allowing for some flexibility of input choice. 10 (a) Nesting in non-fossil fuel production

11. 11 Abatement options in Sust-Rus model (2)  End-of-pipe abatement:  Limited to SO 2, NOx and PM;  Sector-specific estimates for the RF from the IIASA GAINS-Europe model;  Not yet introduced: bottom-up abatement options for CO2 at the sectoral level from Bashmakov et al. (2008) 11

12. 12 Illustrative policy experiment: gas price increases General settings: Time horizon: 2015 Reference scenario (“doing-nothing case”): BaU: Business-as-Usual reference scenario Scenario A Scenario B Scenario C Scenario D consumers: annual gas price increase by 10% from 2012 firms: annual gas price increase by 10% from 2012 consumers & firms: annual gas price increase by 10% from 2012 consumers & selected firms: annual gas price increase by 10% from 2012

13. 13 Energy intensity in 2015 (kgoe/$US) Scenario A: Annual consumer gas price increase by 10% from 2012 onwards will leave country's energy intensity virtually unchanged in 2015 in comparison to “doing-nothing case” 0,48 0,28 0,37 0,35 0,39 0,32 0,39

14.  Robust insight confirmed by other inequality measures such as Gini, Atkinson and Kakwani indices 14 Social impacts (% change in consumption vs. BaU) Scenario A: Annual consumer gas price increase by 10% from 2012 onwards will have a moderate but regressive impact on citizen’s welfare in comparison to “doing-nothing case”

15. 15 Summary: Impact assessment Social impacts (0.4% vs. Bau) Energy intensity (<0.1% vs. Bau) CO2 emissions NOx emissions (0.9% vs. Bau) Tax revenues (0.4% vs. Bau) Public savings (1.5% vs. Bau)

16. 16 Energy intensity in 2015 (kgoe/$US) Scenario B: Energy intensity decreases significantly if sectors face gas price increases (10% annually from 2012 onwards). In comparison to “doing- nothing case, the regional rate of improvement varies between 12% and 14% 0,43 0,25 0,33 0,30 0,34 0,28 0,30

17. 17 Interindustrial impacts (% output changes) in 2015 Scenario B: Moderate output losses for most sectors with few experiencing some improvements in comparison to “doing-nothing case”

18. 18 Social impacts (% in consumption vs. BaU) Scenario B: Firm’s gas price increase (10% from 2012 onwards) will have a moderate and progressive impact on citizen’s welfare in comparison to “doing-nothing case”

19. 19 Environmental impacts - CO 2 (% change vs. BaU) Scenario A + B: Annual gas price increase to be faced by firms (10% from 2012 onwards) will lead to a non-negligible CO 2 reduction in comparison to “doing-nothing case” and Scenario A

20. 20 Conclusions –Identifying policy-relevant robust insights –Providing explanations for differences in impact assessment (data, assumptions) –Identifying high priority areas for future research (“missing gaps”) Sust-Rus model = Rationale basis for equity-efficiency debate Sust-Rus model = first regionally disaggregated model for Russia at the level of federal districts which captures multi-gas emissions

21. Thank you very much for your attention! alexeeva-talebi@zew.de

22. 22 Additional application: Environmental taxation Introduction of environmental levy (CO2 tax) to the economy in 2006: –The amount of the environmental levy is 1€/ton of CO 2, 5€/ton of CO 2 and 10€/ton of CO 2 –Uniform emission pricing, i.e. no differential emission pricing in favour of energy- intensive and trade-exposed industries and no exemptions from taxation; –Recycling mechanism: Revenues are returned to the households via lump-sum transfers;

23. 23 Model results: Sectoral output effects (% change vs. BAU) Heterogeneous effects at the sectoral level: In energy producing sectors up to 10% output losses vs. BAU; Producers of ferrous metals, non-metallic minerals and chemical producers: moderate losses (up to 3% vs. BAU at 10€/ton) ;

24. 24 CO 2 emissions by fuel type in 2005 Economy-wide and sectoral perspective for the RF Sectoral heterogeneity in terms of CO 2 emissions by fuel type: Emissions of manufacturers of wood products, transport equipment and leather products are from combustion of oil and/or coal. Source: Goskomstat TER-Database

25. 25 At 1€/ton, the regional differences in terms of output losses in basic metals production are rather moderate; they become rather pronounced towards higher CO 2 taxes; Sectoral output effects: Basic metals (% change vs. BAU) Value-added of regional disaggregation

26. 26 More homogenous implications in paper industry across regions, except for Ural region; Sectoral output effects: Paper industry (% change vs. BAU) Value-added of regional disaggregation

27. 27 More homogenous implications in paper industry across regions, except for Ural region; Sectoral output effects: Paper industry (% change vs. BAU) Value-added of regional disaggregation

28. 28 – Economy-wide emission reductions: 6.2% (1 €/ton), 21.5% (5 €/ton), 32.4% (10 €/ton) – Significant emissions reduction, in particular in sectors which are known to be the biggest emitters in Russia: energy generation, manufacturing of basic metals and non-metallic minerals; Emissions reduction (% change vs. BAU)

29. 29 Moderate adjustments in exports levels in most sectors, except for power generation; Exports to the EU (% change vs. BAU)

30. 30 Results Key finding: Environmental levies allow reducing CO 2 emissions significantly without sacrificing economy-wide welfare (less than 0.3% for the most ambitious tax level) and international competitiveness of the Russian industry: –significant reductions of CO 2 emissions in key industries such as energy generation, basic metals and non-metallic minerals production are possible (up to 25% vs. BAU); –The scope for significant reductions is consistent with an extensive usage of energy at the sectoral level; –Output effects vary significantly across sectors and regions, but adjustments remain rather moderate, except for the energy producing industry; for example, the output losses in the basic metals production is not likely to be more than 3.5% vs. BAU); an important driver behind the output adjustments is a sectoral heterogeneity in terms of fuel mix; –Exports to the EU are not likely to be heavily adjusted.

31. 31 Outlook Apply to other policy issues: –bottom-up abatement options for CO 2 at the sectoral level from Bashmakov et al. (2008); this allows capturing the technological update of the production facilities; –supply restrictions of gas to the industry – in the mid-term it is intended by the Russian government to rely more heavily on coal; what are the implications? –VOC emissions into the model; –modeling health impacts from air pollution (SO2, NOX, PM, VOC emissions and ozone).